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» Margin based feature selection - theory and algorithms
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JMLR
2010
104views more  JMLR 2010»
13 years 2 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 8 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
ESANN
2006
13 years 9 months ago
On the selection of hidden neurons with heuristic search strategies for approximation
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Ignacio Barrio, Enrique Romero, Lluís A. Be...
BMCBI
2005
118views more  BMCBI 2005»
13 years 7 months ago
Feature selection and nearest centroid classification for protein mass spectrometry
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
Ilya Levner
PAMI
2006
215views more  PAMI 2006»
13 years 7 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...